Chris Lynn will join Yale as an Assistant Professor of Physics, a member of the Quantitative Biology Institute, and a member of the Wu Tsai Institute in 2024. Chris received his undergraduate degrees in Physics and Mathematics in 2014 from Swarthmore College and his Ph.D. in 2020 from the University of Pennsylvania. As a graduate student in Dani Bassett’s lab, he used network science and information theory to study human information processing in cognitive experiments. Chris then completed his postdoc as a James S. McDonnell Foundation Fellow at Princeton, working closely with William Bialek, Stephanie Palmer, and David Schwab to understand the emergence of irreversibility and complex structures in neural systems.
In his research, Professor Lynn aims to distill the inherent complexity of living systems (particularly the brain) to basic underlying principles. In biology and neuroscience, microscopic interactions build upon one another to produce macroscopic behaviors and impressive feats of information processing. To understand how large-scale phenomena emerge from fine-scale interactions, Lynn’s group develops theoretical insights and computational techniques that apply directly to data. Leveraging ideas from statistical physics, network science, and information theory, they investigate how collective patterns of activity and structure emerge and dynamically evolve in neural systems [1-4]; and study how these patterns encode, communicate, and compress information [5-7]. Ultimately, Lynn’s group seeks to understand the statistical mechanics of emergence and information processing in the brain. For reference see selected publications below.
- Christopher W. Lynn & Dani S. Bassett. “The physics of brain network structure, function, and control”. Nat. Rev. Phys. (2019).
- Christopher W. Lynn, Eli J. Cornblath, Lia Papadopoulos, Maxwell A. Bertolero, & Dani S. Bassett. “Broken detailed balance and entropy production in the human brain”. PNAS (2021).
- Christopher W. Lynn, Caroline M. Holmes, William Bialek, & David J. Schwab. “Decomposing the local arrow of time in interacting systems”. Phys. Rev. Lett. (2022).
- Christopher W. Lynn, Caroline M. Holmes, & Stephanie E. Palmer. “Heavy-tailed neuronal connectivity arises from Hebbian self-organization”. Preprint.
- Christopher W. Lynn, Ari E. Kahn, Nathaniel Nyema, & Dani S. Bassett. “Abstract representations of events arise from mental errors in learning and memory”. Nat. Commun. (2020).
- Christopher W. Lynn, Lia Papadopoulos, Ari E. Kahn, & Dani S. Bassett. “Human information processing in complex networks”. Nat. Phys. (2020).
- Christopher W. Lynn & Dani S. Bassett. “Quantifying the compressibility of complex networks”. PNAS (2021).